Adriano Massimiliano Priola1, Sandro Massimo Priola2, Maria Teresa Giraudo3, Dario Gned2, Alessandro Fornari4, Bruno Ferrero5, Lorena Ducco2, Andrea Veltri2. 1. Department of Diagnostic Imaging, San Luigi Gonzaga University Hospital, Regione Gonzole 10, 10043, Orbassano (Torino), Italy. adriano.priola@inwind.it. 2. Department of Diagnostic Imaging, San Luigi Gonzaga University Hospital, Regione Gonzole 10, 10043, Orbassano (Torino), Italy. 3. Department of Mathematics "Giuseppe Peano", University of Torino, Via Carlo Alberto 10, 10123, Torino, Italy. 4. Department of Pathology, San Luigi Gonzaga University Hospital, Regione Gonzole 10, 10043, Orbassano (Torino), Italy. 5. Department of Neurology, San Luigi Gonzaga University Hospital, Regione Gonzole 10, 10043, Orbassano (Torino), Italy.
Abstract
OBJECTIVES: To evaluate the usefulness of diffusion-weighted magnetic resonance for distinguishing thymomas according to WHO and Masaoka-Koga classifications and in predicting disease-free survival (DFS) by using the apparent diffusion coefficient (ADC). METHODS: Forty-one patients were grouped based on WHO (low-risk vs. high-risk) and Masaoka-Koga (early vs. advanced) classifications. For prognosis, seven patients with recurrence at follow-up were grouped separately from healthy subjects. Differences on ADC levels between groups were tested using Student-t testing. Logistic regression models and areas under the ROC curve (AUROC) were estimated. RESULTS: Mean ADC values were different between groups of WHO (low-risk = 1.58 ± 0.20 × 10(-3)mm(2)/sec; high-risk = 1.21 ± 0.23 × 10(-3)mm(2)/sec; p < 0.0001) and Masaoka-Koga (early = 1.43 ± 0.26 × 10(-3)mm(2)/sec; advanced = 1.31 ± 0.31 × 10(-3)mm(2)/sec; p = 0.016) classifications. Mean ADC of type-B3 (1.05 ± 0.17 × 10(-3)mm(2)/sec) was lower than type-B2 (1.32 ± 0.20 × 10(-3)mm(2)/sec; p = 0.023). AUROC in discriminating groups was 0.864 for WHO classification (cut-point = 1.309 × 10(-3)mm(2)/sec; accuracy = 78.1 %) and 0.730 for Masaoka-Koga classification (cut-point = 1.243 × 10(-3)mm(2)/sec; accuracy = 73.2 %). Logistic regression models and two-way ANOVA were significant for WHO classification (odds ratio[OR] = 0.93, p = 0.007; p < 0.001), but not for Masaoka-Koga classification (OR = 0.98, p = 0.31; p = 0.38). ADC levels were significantly associated with DFS recurrence rate being higher for patients with ADC ≤ 1.299 × 10(-3)mm(2)/sec (p = 0.001; AUROC, 0.834; accuracy = 78.0 %). CONCLUSIONS: ADC helps to differentiate high-risk from low-risk thymomas and discriminates the more aggressive type-B3. Primary tumour ADC is a prognostic indicator of recurrence. KEY POINTS: • DW-MRI is useful in characterizing thymomas and in predicting disease-free survival. • ADC can differentiate low-risk from high-risk thymomas based on different histological composition • The cutoff-ADC-value of 1.309 × 10 (-3) mm (2) /sec is proposed as optimal cut-point for this differentiation • The ADC ability in predicting Masaoka-Koga stage is uncertain and needs further validations • ADC has prognostic value on disease-free survival and helps in stratification of risk.
OBJECTIVES: To evaluate the usefulness of diffusion-weighted magnetic resonance for distinguishing thymomas according to WHO and Masaoka-Koga classifications and in predicting disease-free survival (DFS) by using the apparent diffusion coefficient (ADC). METHODS: Forty-one patients were grouped based on WHO (low-risk vs. high-risk) and Masaoka-Koga (early vs. advanced) classifications. For prognosis, seven patients with recurrence at follow-up were grouped separately from healthy subjects. Differences on ADC levels between groups were tested using Student-t testing. Logistic regression models and areas under the ROC curve (AUROC) were estimated. RESULTS: Mean ADC values were different between groups of WHO (low-risk = 1.58 ± 0.20 × 10(-3)mm(2)/sec; high-risk = 1.21 ± 0.23 × 10(-3)mm(2)/sec; p < 0.0001) and Masaoka-Koga (early = 1.43 ± 0.26 × 10(-3)mm(2)/sec; advanced = 1.31 ± 0.31 × 10(-3)mm(2)/sec; p = 0.016) classifications. Mean ADC of type-B3 (1.05 ± 0.17 × 10(-3)mm(2)/sec) was lower than type-B2 (1.32 ± 0.20 × 10(-3)mm(2)/sec; p = 0.023). AUROC in discriminating groups was 0.864 for WHO classification (cut-point = 1.309 × 10(-3)mm(2)/sec; accuracy = 78.1 %) and 0.730 for Masaoka-Koga classification (cut-point = 1.243 × 10(-3)mm(2)/sec; accuracy = 73.2 %). Logistic regression models and two-way ANOVA were significant for WHO classification (odds ratio[OR] = 0.93, p = 0.007; p < 0.001), but not for Masaoka-Koga classification (OR = 0.98, p = 0.31; p = 0.38). ADC levels were significantly associated with DFS recurrence rate being higher for patients with ADC ≤ 1.299 × 10(-3)mm(2)/sec (p = 0.001; AUROC, 0.834; accuracy = 78.0 %). CONCLUSIONS: ADC helps to differentiate high-risk from low-risk thymomas and discriminates the more aggressive type-B3. Primary tumour ADC is a prognostic indicator of recurrence. KEY POINTS: • DW-MRI is useful in characterizing thymomas and in predicting disease-free survival. • ADC can differentiate low-risk from high-risk thymomas based on different histological composition • The cutoff-ADC-value of 1.309 × 10 (-3) mm (2) /sec is proposed as optimal cut-point for this differentiation • The ADC ability in predicting Masaoka-Koga stage is uncertain and needs further validations • ADC has prognostic value on disease-free survival and helps in stratification of risk.
Entities:
Keywords:
Apparent diffusion coefficient; Diffusion-weighted magnetic resonance imaging; Masaoka-Koga staging system; Thymoma; WHO classification
Authors: S Novello; C Fava; P Borasio; L Dogliotti; G Cortese; B Crida; G Selvaggi; P Lausi; M P Brizzi; P Sperone; L Cardinale; F Ferraris; F Perotto; A Priola; G V Scagliotti Journal: Ann Oncol Date: 2005-07-08 Impact factor: 32.976